Our use cases include connecting a lot of legacy data systems to our logical components. For example, if somebody has a question that they post to us and say, "Tell me everywhere in our organization where we have a policy stored?" the primary use case is to logically define what a policy is, and then we use Collibra to tie that logical construct to a technical implementation. We may have six or eight, however many, different admin systems. We bring in the schemas of the way that those systems look, and then how a policy exists in this database and this table and this column, for example, in that legacy system.
The second use case that we implement is the ability to track the provenance or the lineage as to how something changes over time. For example, if we bring data in from a legacy system and we use some tool set (e.g. Azure Data Factory) to extract the data into a Hadoop data lake, and then perform some transformations on it, we want to be able to track it; "It came from the source system here, and this field got changed to this name, and we applied this transformation on this field and it eventually shows up on this report here."
We use it to track where a policy exists and also how it got there: it exists on this report and here's how it got on that report, here are all the steps that it took getting through to that particular report from the actual source system itself. Because quite often what we're finding is that our business users will get a report and they'll say, "I think your report's wrong. How did you get that value on that report?" That provenance or lineage is what helps answer those questions.
We have data stewards who are the resources that if somebody proposes a new logical asset based on what they think the customer means, these data stewards are the ones that would get together and look at what's being proposed and make sure it works across all of our business units for a generic implementation, or create business unit specific terms if required. They're the ones that say a particular system or term or logical construct is ready for consumption by end users.
Another group we have is the end users. We try to have people use Collibra by asking, "Don't tell me what system you want to get access to, tell me what you're looking for in business terms/constructs." In our example, it would be the question, "Tell me about all the policies in our system." They would go to Collibra and "shop" for that data and pick a policy and put it into the shopping cart basket that Collibra provides as part of their interface. Then they would submit that request for approval/access to the underlying data.
We also have data stewards who approve the use of new/updated business terminology and end users who are looking for their data to make business decisions. We also have some power users who are the resources who are setting the direction for the application of where we want to go with it, (e.g. new workflows or new functionality within Collibra).
For us, the Collibra application is an on-premise installation (although we use IaaS VMs to host it on cloud); it is not their SaaS implementation.